Predictive Analytics for farmers and agriculture business
The agriculture business industry in developing countries is characterized by infrastructure shortages, an under-developed processing industry, series of recent de-regulations and a renewed focus on research to evolve a more professional approach from ‘farm to fork’. While doing so, some of the key agriculture business marketing related issues that need to be addressed are:
Segmentation of agri-markets based on crops grown / pricing / farm size / lease terms
Identification and assessment of all the stakeholders on the supply side – farmer, village commission agent, district commission agent, wholesaler, sub-wholesaler, the retailer
Optimizing storage and warehousing locations
Optimize mechanization – the spread of farms vs farm yield
Classifying markets based on the degree of progressiveness, especially infrastructure
Streamlining the marketing chain – cold storage, distribution – to ensure ‘freshness’ of end-product
Identify pockets of yield-conscious & wellness-inclined farmers for premium offerings
Why big data crucial for agriculture?
It is not the amount of data that is important, it is what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions to drive competitive advantage. It, therefore, offers great opportunities in agriculture which include:
Vast potential to increase productivity and innovation
The McKinsey Global Institute states that big data has the potential to “transform economies, delivering a new wave of productivity”. In the process, it will change the basis for competition and presents substantial opportunities for those with the capabilities to exploit the potentially highly-valuable insights available. Within agriculture, as global food demand is projected to double by 2050 due to rising populations, farmers and agricultural suppliers will increasingly be expected to do more with less by increasing productivity from limited resources and inputs. Due to these pressures, innovative technologies such as Precision Farming will play a major role in the development of agriculture and will present a multitude of opportunities to farmers to adapt their practices and input applications to inter and intra-field variability in crops. For crop protection suppliers, this means that products could be applied in a multitude of dose rates and tank mixes within a single field. As a result, the broad-brush approach of conventional analysis techniques (e.g. surveys undertaken post-application) will become increasingly redundant and unreliable.
Real-time insights to help performance optimization
Advanced analytics can show how farmers are utilizing their inputs and what adaptations are required to take account of emerging weather events or disease outbreaks. The key challenge will be to deliver such real-time insights clearly and concisely to enable effective decision-making. To achieve this, advanced algorithms are needed to swiftly unlock the highly valuable insights available from big data so that products are performing to expectations on an ongoing basis despite changing conditions.
The development of highly specific customer segmentation
It has become possible to tailor product offerings to precisely meet customer needs as they evolve. For instance, if Black Grass becomes problematic in a given region, suppliers can deploy big data techniques such as real-time micro-segmentation of customers to target promotional and marketing activities, thus facilitating better utilization of marketing spend. Such analytics would also facilitate the development of more sophisticated pricing strategies that better match price and value at the segment level.
Data becoming a major source of competitive advantage
Big data connectivity has proven itself a key asset for companies seeking a competitive advantage over their competitors. Benefits included are the faster unearthing of valuable insights, and the ability to develop and adapt products that meet specific customer needs on an ongoing basis. Competitors that fail to develop or gain access to sophisticated analytics expertise will be left behind. Big data has already changed the way we do business. The rise of new technologies in the agricultural sector offers a chance for all businesses to better harness their data and convert their processes. Connectivity between systems and businesses has the potential to drive a surge in profitability and more efficient practices for the whole supply chain. Big data is here to stay, and businesses that seize the full array of benefits on offer will put themselves at a competitive advantage for the future.
Credits: Originally appeared in Proagrica https://proagrica.com/news/how-big-data-will-change-agriculture/
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